I have different measurements from two+ sensors. I want to compare the performance of each sensor for each measurement with errorbars (mean and std). I have no problems creating and formatting a standard errorbar plot for one y (sensor) and yerr per data point (measurement). But i'm trying to create a plot like this:
I can neither find the option to do this in the matplotlib documentation nor when i google it or search this site. The closest i found was this thread:
matplotlib: grouping error bars for each x-axes tick
But this solution doesn't work for me since my datapoints aren't numbers but a pandas dataframe index of strings.
So i found the solution in the Matplotlib documentation after all. Here's the link for people who might have the same question:
A bar plot with errorbars and height labels on individual bars.
I make a plot with different subplots (using gridspec.GridSpec). Two subplots share the same x-axis (sharex=ax1 in the definition of the second subplot).
However, as one subplot shows the indices of the chronologically sorted data, and the second subplot shows the corresponding decades, I want seperate ticks and labels for the x-axes of both plots. This seems not possible, a unique set of labels and ticks are assigned to both subplots. Until now, I can only:
use different x-axes and thus assign two sets of ticks and labels.
In that case, the axes are not alligned although
ax1.set_xlim([start, stop]) are similarly defined for both subplots
use a common x-axis and one set of ticks and labels
I do not find a solution for this on the internet. Is someone able to help? Thank you in advance!
I am really pretty new to matplotlib, though I know that it can be very powerful.
I've been reading number of tutorials and examples and it's a real hassle to understand how does matplotlib's Figure and Axes work. I am illustrating, what I am trying to understand, with the attached figure.
I know how to create a figure instance of certain size in inches. However, what bothers me is how can I create subplots and then axes, within each subplot, with relative coordinates (bottom=0,left=0,top=1,right=1) as illustrated.
So, for example I want to create a "parent" plot area (say (6in,10in)). Then, I want to create two subplot areas, each with size (3in,3in), with 1in space from the top, 2in space between the two vertical subplot areas and 1in from bottom. Then, 1in space on the left and 2in space on the write. In the same time, I would like to be able to get the coordinates of the subplot areas with respect to the main plot area.
Then, inside the first subplot area, I'd like to create 2 axis instances, with Axis 1, having coordinates with respect to Subplot Area1 (0.1,0.7,0.7,0.2) and Axes 2 (0.1,0.2,0.7,0.5). And then of course I'd like to be able to plot on these axes e.g., ax1.plot()....
If you could provide a sample code to achieve that, then I can study it.
Your help will be very much appreciated!
a subplot and an Axes object are really the same thing. There is not really a "subplot" as you describe it in matplotlib. You can just create your three Axes objects using gridspec without the need to put them in your "subplots".
There are a few different ways to create Axes instances within your figure.
fig.add_axes will create an Axes instance at the position given to it (you give it [left,bottom,width,height] in figure coordinates (i.e. 0,0 is bottom left, 1,1 is top right).
fig.add_subplot will also create an Axes instance. In this case, rather than giving it a rectangle to be created in, you give it the number of rows and columns of subplots you would like, and then the plot_number, where plot_number starts at 1, increments across rows first and has a maximum of nrows * ncols.
For example, to create the top-left Axes in a grid of 2 row and 2 columns, you could do the following:
fig.add_subplot(2,2,1)
or the shorthand
fig.add_subplot(221)
There are some more customisable ways to create Axes as well, for example gridspec and subplot2grid which allow for easy creation of many subplots of different shapes and sizes.
I have a four dimensional data set. None of the four variables are equally spaced. Right now, I visualize the data using 3D scatter (with the color of the dots indicating the fourth dimension). But this makes it extremely unwieldy while it is printed. Had the variables been evenly spaced,a series of pcolors would have been an option. Is there some way, wherein I can represent such a data using a series of 2D plots? My data set looks something like this:
x = [3.67, 3.89, 25.6]
y = [4.88, 4.88, 322.9]
z = [1.0, 2.0, 3.0]
b = [300.0,411.0,414.5]
A scatter plot matrix is a common way to plot multiple dimensions. Here's a plot of four continuous variables colored by a fifth categorical variable.
To deal with the uneven spacing, it depends on the nature of the unevenness.
You might plot it as-is if the unevenness is significant.
You might make a second plot with the extreme values excluded.
You might apply a transformation (such as log or quantile) if the data justifies it.
I have a lineplot with 2 lines on it...they're two separate channels from the same data set. Would love to just label each one - the "labels" options are all about giving a number for each point on your plot, and that is simply not helpful.
Would love to know how to do any (really, all, but I just need to do one to be happy) of these:
plot each against its own y axis and be able to sensibly label that axis with units (and color the numbers to correspond to the data it correlates to)
put a legend on it. I can't figure out how to use lineLegend
just put any kind of (singular) label in the vicinity of the lines.